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I have been enthusiastic about telomerase therapies for anti-aging since 2003. But if I can’t change my mind as new data appears, what’s the point of being a scientist? I still believe that lengthening telomeres is a net benefit, but the potential for added years is modest, and there are probably risks and tradeoffs. The study that has most influenced me is this one, implying that telomerase affects epigenetics (through methylation) in ways that accelerate aging. My theory is that the unexpected relationship between telomerase and methylation is an example of antagonistic pleiotropy, but pleiotropy in a very different sense from the standard evolutionary theory.

Do people with longer telomeres have longer life expectancy? In 2003, Richard Cawthon of University of Utah first addressed this question experimentally with a study that was clever, innovative and courageous. It was innovative in that he introduced a fast and convenient way to measure telomere length from very small quantities of DNA, using the Polymerase Chain Reaction. It was clever in that, instead of a “prospective study” measuring telomere length in his subjects and then following 20 years to see what would happen to them, he did the experiment retrospectively, using historic samples of blood that had been taken from people twenty years earlier and kept in frozen storage by a local hospital. And it was courageous in that everyone believed at the time that extending life could not be so easy as just lengthening telomeres, or else the body would already be doing it! That is to say, no one would fund the study because they thought they knew how it had to come out.

But they were wrong. Even with Cawthon’s small sample of only 143 subjects, the relationship between telomere length and diseases of old age jumped out of the statistics. The quartile with the shortest telomeres had suffered two times higher mortality and three times greater incidence of heart disease in the intervening 20 years than those with the longest telomeres.

Red blood cells have no DNA, hence no telomeres, but white blood cells are constantly dividing to target specific bacterial, so the telomeres in white blood cells are a sensitive measure of immune health. Cawthon reported that the group with shortest telomeres had suffered 9 times the rate of infectious disease compared to the longest telomere group.

At the time of Cawthon’s study, there was a great deal of skepticism, based purely on theory. The standard hypothesis was that all animals are evolved to live as long as possible, all else being equal, and if telomerase were being held back, there must be a powerful downside associated with it. I was already marching to the beat of a different drummer in 2003, and I didn’t believe that evolution was always going for the longest lifespan available. Because I believe that aging is an evolutionary program, it was easy for me to see telomere shortening as part of the program. The biggest clue in my mind was the evolutionary origin of telomere shortening in single-celled protozoans. In the ciliates (e.g. paramecium), telomerase is not expressed in mitosis (when the cell copies itself), but only when it conjugates (recombining genes with other individuals) with another. Hence, a cell that just goes on reproducing as fast as possible without sharing its genes was doomed to die of cell senescence. A billion years ago, telomeres were already a means of enforcing the communal imperative, Share your genes! It is easy to imagine that the same evolutionary imperative has persisted through the aeons, and that telomere shortening insures death in many higher organisms. Indeed, since Cawthon, it has been demonstrated that short telomeres are a mode of aging in dogs, cats, and horses, (but not cows, pigs or mice).

Three years ago, I reported on a Danish study that replicated Cawthon’s results on a huge scale. In 60,000 subjects, Rode associated short telomeres with all-cause mortality, heart disease, diabetes, and some cancers.

Telomere shortening leads to senescence and higher disease risk by three known mechanisms. First, stem cells with the shortest telomeres stop reproducing, hence the body’s tissues don’t renew as efficiently. Second, senescent cells are not just dead weight, they actually emit chemical signals (cytokines) that increase inflammation. This has been called SASP, for Senescence-Associated Secretory Phenotype.) Third, senescence in the bone marrow that generates new white blood cells is especially damaging to the immune system, because it prevents the body from responding effectively when challenged with new infections.

Telomeres and cancer

If short telomeres cause all these problems, why would the body ever allow its telomeres to become short? It was recognized early in the game that production of telomerase entails no substantial metabolic cost, so the question challenges the conventional theory that individual animals are evolved to live as long as possible. Of course, for us who believe that aging is programmed, there is no problem with this. But the first suggestion of an answer within the conventional paradigm came from Carol Greider, one of the original discoverers of telomerase, and independently from Ruth Sager. Telomerase is needed to make cells immortal. 90% of cancer cells have found ways to bypass the suppression of telomerase in order to continue proliferating unabated. Greider and Sager proposed that keeping telomerase under lock and key constitutes one of the barriers that keeps cells from going rogue as tumors. Telomere shortening helps to prevent cancer.

This argument never made any sense to me. First, what good was it to suppress cancer if the net effect was to shorten lifespan? And second, I believe that the body’s principal defense against cancer is the immune system, and if short telomeres can cripple the immune system, that was likely to do more to promote cancer than to prevent it.

Nevertheless, the idea that telomerase is rationed to protect against cancer persisted in the biomedical community for 20 years based on theory alone, even as it was moderated by the discovery of SASP.

Experimental link between telomeres and cancer

I came into this field very skeptical of the idea that long telomeres could cause cancer. But as the evidence has accumulated, I’m compelled to reconsider. Just last summer, I blogged critically about the largest genetic study to date, linking genetic predisposition for longer telomeres with cancer rates later in life. I noted that the measured effect is actually quite small, but is reported blown up to alarming proportions by exponential extrapolation. But that didn’t mean it was necessarily wrong, only that it was unconvincing. Shortly afterward, I became aware of observational studies, based on measured telomere length rather than the genetic predisposition. These are harder to refute.

In this study from the Moffitt Cancer Center, short telomeres (as measured directly, not imputed from genetic variation) are associated with higher risk of squamous cell skin cancer, but long telomeres are associated with higher risk of melanoma skin cancer. Same methodology, same authors. Why would I believe one and disbelieve the other? Melanoma tends to occur at younger ages than squamous cell carcinoma, this supporting the Greider hypothesis that telomere shortening should be especially important for cancer prevention while we are still in a fertile stage of life. The Moffitt results on melanoma were confirming a finding reported earlier from Harvard Med School.

In this study, people with the longest telomeres had nearly twice the risk of lung cancer compared to people with short telomeres, after adjustment for age and smoking status. There are 25 co-authors, and Cawthon is #2. In this study, short telomeres protect against (devastatingly lethal) pancreatic cancer, and in this one, there is an elevated risk of breast cancer associated with long telomeres.

There are studies contradicting each of these findings. Overall, the field seems to be more of a confused mess even than most areas of epidemiology. But for lung cancer, melanoma, and pancreatic cancer, the predominance of the evidence says that longer telomeres are associated with higher risk.

Longer telomeres uncontroversially protect against heart disease and stroke. There is no contradiction of this finding in sight, and there has been no contradiction of the major finding (by Rode and Cawthon) that short telomeres increase all-cause mortality. Perhaps that’s all we need to know.

Stop the Presses

Just a few weeks ago, I learned of this new study linking telomerase to the epigenetic changes that the methylation clock associates with aging. The implication is that telomerase accelerates aging. It began with an investigation by Steve Horvath’s group (about which I reported last month) asking, what genetic variations are associated with people who age faster or slower than average, according to the Horvath methylation clock? They did a genome-wide search for statistical correlates and the standout association was telomerase. People who have small genetic variations that support greater telomerase expression tend to have longer telomeres, but they also tend to age faster, as measured by the Horvath clock.

It’s been known for a long time that telomerase has other effects in addition to lengthening telomeres. But this is the first time that telomerase has been reported to affect DNA methylation. So it seems we are presented with a tradeoff, or pleiotropy, or Catch-22, or “damned if you do, damned if you don’t.”

The association between telomerase and accelerated aging (measured by methylation) was found in the genetic statistics, and then confirmed in a cell culture. When telomerase was artificially activated in the cell culture, the methylation patterns changed in the cells consistent with older age according to the Horvath clock. In fact (and remarkably in my opinion) they found no Horvath aging at all in the cell cultures that lacked telomerase. Could it be that telomerase is the one and only driver of epigenetic aging at the cellular level?

Telomere length and the Horvath methylation clock are both correlated with age, but they are not otherwise correlated with each other. The Horvath clock is a combination of 353 methylation levels that is optimized to correlate maximally with age. The observed correlation is 0.95. Telomere length is not statistically optimized but measured as nature offers it, and its correlation is much weaker (~0.4 according to my estimate, as I have not found this number in print). Thus Horvath clock is an excellent measure of chronological age, and combining information about telomere length can make it potentially a little more accurate yet. But the telomere clock on its own is a very unreliable measure of age.

The Horvath group designed an experiment to separate the direct effect of telomerase on methylation from an indirect effect (telomerase ⇒ telomere length ⇒ methylation age). They found no indirect effect. Telomerase itself affects methylation aging, but telomere length does not.

This raises (what is for me) an uncomfortable question. Many “good” life habits have been associated with telomerase expression, including exercise, meditation, and social integration. Could it be that these habits are simultaneously slowing our telomere aging, while hastening our epigenetic aging?

“While the paradoxical finding cannot be disputed on scientific grounds, its biological interpretation remains to be elucidated.” [Lu et. al, 2018, the same study I’ve been talking about]

(Another finding of this same study: Earlier menopause is associated with epigenetic age acceleration in women, but this is mitigated by hormone replacement therapy. HRT modestly slows aging, as measured by the Horvath clock.)

Antagonistic Pleiotropy is the standard explanation for aging, though I have long argued that it doesn’t fit the data. The theory says that some genes enhance fertility and survival early in life, but have detrimental effects late in life. These genes are selected in a Darwinian process because their benefits outweigh their costs. Even though they die younger, those individuals carrying the pleiotropic genes leave more offspring, and that’s what counts for evolution. The crux of the theory is that nature is caught between Scylla and Charybdis, forced by limitations of the available genes to choose either high fertility with short lifespan or low fertility with longer lifespan. Crucial to the theory is the assumption that it is biologically impossible to separate the benefits of these pleiotropic genes (fertility) from their costs, so that there is no way evolution could engineer higher fertility without triggering later senescence.

This theory was formulated by George Williams in 1957, long before anyone had heard of epigenetics. He assumed that if you have a gene, you’re stuck with it for life. We can’t blame Williams for the frame of mind that he brought to the evolutionary question, but we now know that this is very much not the case. The body turns genes on and off in individual tissues and at specific times with exquisite precision. In fact, most of the euklaryotic genome is devoted not to genes, but to epigenetic controls of one kind or another.

The fact is that genes are turned on that dial up fertility and promote robust replacement cell growth early in life, and aging at that time occurs quite slowly. Later in life, these growth and fertility genes are dialed way back, and that is the era in which aging comes at us with a vengeance. This, to me, is a direct refutation of Antagonistic Pleiotropy as a theory.

Nevertheless, many examples pleiotropic genes have been found in studies of aging. The above story of telomerase seems to be a conspicuous example. Telomerase promotes epigenetic aging, while lack of telomerase promotes cellular senescence. “If the ’skeeters don’t getcha then the gaitors will.”[ref]

My interpretation of pleiotropy is in my book and some of my academic papers. It is this: Aging has been built into our genomes by natural selection for the sake of the community. Fixed lifespan, (especially when modified conditions of food stress) is helpful in preventing population overshoot that can lead to famines, epidemics, and extinction. But whenever a trait is good for the community and bad for the individual, there is a temptation for the individual to cheat (“cheating” is actually the term used by evolutionary theorists). In this case, cheating would mean evolving a longer lifespan via selfish genes that spread rapidly through the population, because they are more successful at the lowest level of Darwin’s competition.

Individual competition would erase aging if left unchecked. The results would be great for individual fitness, but soon would be disastrous for the population. Overpopulation would ensue, followed by the famines and epidemics mentioned above. Evolution has learned (over a very long expanse of time) to protect the communal interest, placing barriers in the way of individual selection for ever longer lifespan. This is the evolutionary significance of pleiotropy. It provides that no simple mutation can substantially extend any aspect of lifespan without adversely affecting another aspect of lifespan or of fertility. The aging clock has been “purposely” configured so as to be spread out over several different mechanisms, tied not just to other pro-aging mechanisms but to fertility as well. Aging is hard to get rid of “by design”.

In the standard theory that I don’t believe, antagonistic pleiotropy is a precondition, and evolution has had to make the best of a bad deal. In my version, antagonistic pleiotropy has been crafted by natural selection in its long-term mode. Limiting lifespan has been so important to the viability of the population that evolution has arranged to protect it from leaking away due to cheating, and antagonistic pleiotropy is one of the ways in which this is arranged. I have modeled this process in numerical simulations of evolution.

My guess is that the connection between telomerase and epigenetic aging is an example of antagonistic pleiotropy in this latter sense–certainly not in the sense of Williams, because on their face telomerase and methylation have little to do with one another.

Bad news for life extension strategies

But whatever the theoretical origins, the pleiotropic connection between telomerase and epigenetic aging complicates any strategy we might devise for slowing the progression of human aging.

I believe that the preponderance of evidence still indicates that activating telomerase has a net benefit for lifespan, but that probably we can add at most a few years by this route. I think that epigenetics is much closer to the core, the origin of aging, and that interventions to modify epigenetic aging will eventually be our holy grail. The caveat is that telomeres are simple, but methylation is complicated, and methylation is just one of many epigenetic mechanisms.

Methylation of DNA is the best-known mode of epigenetic regulation (turning genes on and off). Methylation patterns are stable unless they are actively changed, and can persist over decades, even across generations.

Four years ago, biostatistician Steve Horvath of UCLA identified a set of 353 methylation sites that are best-correlated with human (chronological) age. These are sites where genes are turned on and off at particular stages of life. A computer analysis of a gene sample (from blood or skin or even urine) can determine a person’s age within about two years.

Two reasons the Horvath Clock is important. First, it is the best measure we have of a person’s biological age, so it provides an objective measure of whether our anti-aging interventions are working. Say you’re excited about a new drug and you want to know whether it really makes people younger. Before the Horvath clock, you had to give it to thousands of people and wait a long time to see if fewer of them were dying, compared to people who did not get the drug. The Horvath clock is a huge shortcut. You can give the drug to just a few people and measure their Horvath (methylation) age before and after. With just a few dozen people over a two-year period, you can get a very good idea whether your drug is working.

Second, there is evidence and theory to support the idea that the methylation sites that Horvath identified are not just markers of aging but causes of aging. That means that if we can figure out how to get inside the cell nucleus and re-configure the methylation patterns on the chromosomes, we should be able to address a root cause of aging. (Before we get too excited: “Gene therapy” has been around 20 years but is still in a developmental stage; “epigenetic therapy” is what we need, and it does not yet exist, but is technically feasible using genetically engineered viruses and CRISPR.)

In 2012-2013, three papers appeared proposing the idea that the deep cause of aging (in humans and many other higher animals) is an epigenetic program [Johnson, Mitteldorf, Rando]. Genes are turned on and off at various stages of life, producing growth, development and aging in seamless sequence. (A fourth paper by Blagosklonny proposed a similar idea, but focused on the role of a single transcription factor controlling gene expression (mTOR) and shied away from the conclusion that natural selection might have preferred aging affirmatively. Here’s an earlier presentiment by Blagosklonny.)

It’s a powerful hypothesis that proposes to resolve evolutionary and metabolic questions alike. It contains a seed of a prescription for anti-aging research—although epigenetics has proved to be so complicated that practical modification of the body’s gene expression schedule may require a lot more groundwork.

Unbeknownst to any of us working on these theoretical papers, Steve Horvath was already working on calibration and measurement of the epigenetic aging clock, and he published his basic result by the end of 2013.

One remarkable property of the Horvath clock is that it is more accurate than chronological age for predicting who will contract aging diseases and who will die. Even though the clock was derived with an algorithm that matched the output clock age as closely as possible to chronological age, the result proved to contain more information than chronological age. “In deriving the clock, chronological age was used as a proxy for biological age.” People whose “methylation age” is greater than their chronological age are likely to suffer health deterioration and to die sooner than people whose methylation age is less than their chronological age.

Horvath has openly shared his methodology and his computer program. Based on the Horvath clock, a California company began last year to offer a commercial test for methylation age. You can send a blood or urine sample to Zymo Research.

Candidate aging clocks

Horvath describes how he came up with the idea of a methylation clock by a process of elimination, beginning with four candidate clocks:

Telomere length

Gene expression profile

Proteomic data

DNA Methylation

In detail:

Telomere length – This had been measured easily and cheaply for more than a decade, but its correlation with chronological age (and with mortality) is not strong enough to be useful as a biological clock.

Gene expression profile: Which genes are being transcribed into RNA at a given time? This can be measured by extracting RNA, and turns out to be highly tissue-specific. In other words, it varies according to which part of the body you’re looking at.

Proteomic data: Genes, once transcribed, are translated into proteins. Some of these proteins stay in the cell while others circulate through the body. Gene CHIP technology measures levels of different proteins reliably and inexpensively.

DNA Methylation: Easier to measure than (2) or (3). Methylation is only one of many mechanisms controlling gene expression, but it is one of the most persistent. Horvath found that a subset of DNA methylation sites seems to be characteristic of age no matter where in the body they are measured.

What is DNA methylation?

Adjacent to many genes is a promoter site, a location on the same chromosome which stores temporary information about whether the gene is turned on or off. Promoter sites contain the base sequence C-G-C-G-C-G-C repeated. This is called a CpG island (where the “p” just tells you that the C is linked to G on the same strand, rather than being linked across strands, in which C is paired with G.)

C stands for “Cytosine”, and the Cytosine molecule can be modified by adding an extra methyl group (CH3) to form 5-methyl Cytosine.

The cell has molecular workers that are deployed to go around specifically adding methyl groups in some parts of the DNA or removing them in others. The bottom line is that methylated Cytosine is a sign that says “don’t transcribe the adjacent gene.” When the methyl groups are removed, it is a signal that the gene are to be transcribed once more.

Enzymes called methyl transferases are deployed to precise regions of the genome to turn genes on and off. Methylation can be transient. There is evidence for circadian cycles of methylation. Or it can be quite long-lasting. Methylation patterns can persist for decades, and are copied when cells replicate, so that methylation patterns can be passed to offspring as part of one’s epigenetic legacy. Inherited methylation sites are the exception however; most of the genome is programmed fresh with age-zero, pluripotent methylation patterns when egg and sperm cells are generated.

How the methylation clock works

Using a standard statistical algorithm, Horvath identified 353 CpG sites that were most strongly correlated with chronological age, no matter where in the body he looked. The same algorithm provided 353 numbers to be multiplied by methylation levels at each site, then added up to produce a number. The number is not directly a measure of age, but in the last step a table is used (an empirically-derived curve) to associate the number with an age.

This is the raw output of the function before it is transformed into an age. Notice that methylation changes very rapidly during the first 5 years of life, gradually slowing during the growth phase and straightening out to constant slope after about age 18.

Even though the Horvath clock was designed to be independent of what part of the body DNA was drawn from, some variations appear. Most noticeable is female breast tissue, which ages faster than the rest of the body, and brain tissue, which ages more slowly. Blood and bone tissue tend to age a little faster. (Sperm and egg cells are “age zero” no matter the age of the person from whom the germ cells were drawn. Placentas from women of all ages are age zero.) Similarly, induced stem cells (using the 4 Yamanaka factors) have zero age. In contrast, a similar treatment can change one differentiated cell type into another, for example, turning a skin cell into a neuron. This does not affect epigentic age.

Liver cells tend to be older than the rest of the body in people who are overweight, and younger than the rest of the body in people who are underweight. Other tissues don’t seem to show this relationship. For example, fat cells do not have older methylation ages in people who are obese. And, perhaps surprisingly, weight loss does not reverse the accelerated methylation age of the liver (at least, not within the 9-month time frame of the one study looking at this).

Studies have been done correlating methylation age with various diseases and, of course, mortality. Corrections are made for every kind of environmental factor, including smoking, obesity, exercise, workplace hazards, etc, called collectively the “extrinsic factors”. The result is that methylation age rises with extrinsic factors, and independently methylation age is also correlated with intrinsic (genetic) factors that affect lifespan. Horvath estimates that genetics controls 40% of the variation in methylation age (as it differs from chronological age).

Men are slightly older than women in methylation age. This is already evident by age 2. Delayed menopause is associated with lower epigenetic age. Cognitive function correlates inversely with methylation age of the brain.

Speaking before Horvath at the same conference, Jim Watson claims there are many supplements and medications that can slow the Horvath clock. The one he focuses on is metformin, which, he says, has epigenetic effects via an entirely different pathway from lowering blood sugar (the purpose for which it has been prescribed to tens of millions of diabetics).

Here’s a curious clue: There is a tiny number of children who never develop or grow, and continue to look like babies through age 20 and perhaps beyond. These children have normal methylation age. Whatever it is that blocks their growth, it is not the methylation changes in their DNA. Does this mean that there are other epigenetic controls, more powerful than methylation, that control growth and development? Or does it mean that children with this syndrome have normal epigenetic development, but something downstream from gene expression is blocking their growth? Conversely, Hutchinson-Gilford progeria is caused by a defect in the LMNA gene which causes children to age and die before they even grow up. Hutchinson-Gilford children have normal methylation ages by the Horvath clock.

Radiation, like smoking and exposure to environmental oxidation, tends to age the body faster. This is independent of methylation age—which is unaffected by radiation. Neither smoking nor radiation exposure affect epigenetic age. HIV also accelerates aging, and HIV does affect methylation age.

Methylation age and telomere age are both correlated with chronological age, and they both predict mortality and morbidity independent of chronological age. But the two measures are not correlated with each other. In other words, the information contained in the methylation clock and in measures of telomere length complement one another to offer a better predictor of future aging decline than either of them separately.

Diet has a weak effect on methylation age. Very high carbohydrate, very low protein diets are noticeably terrible. Beyond this, there seem to be two sweet spots: one for the Ornish-style protein-restricted diet and one for the Zone/Atkins style diet. Weak evidence to be sure, but suggestive that they both work.

The original clock was optimized to track chronological age, and yet it fortuitously provided more information than chronological age. In a second iteration, Horvath set out explicitly to track biological age. He used historic blood samples from the 1990s, and paired them with hospital records and death certificates to search for methylation sites that correlate best with aging-related health outcomes. The result was the phenotypic clock, DNAm phenoAge. This uses 513 methylation sites to predict

all-cause mortality

cardiovascular mortality

lung disease

cancer

diabetes

(loss of) physical strength

(loss of) cognitive ability

On the drawing board: An epigenetic clock specialized to work well with skin and blood cells, (which are the most accessible). (Enough skin cells can be scraped painlessly from the inside of your mouth (buccal epithelial cells) to do a DNAm test.)

Connection to Parabiosis and Plasma Transfusions

Several groups have begun to experiment with transfusions of blood plasma from a young donor as a possible path to rejuvenation. Horvath reports an encouraging finding: Sometimes older people contract a form of leukemia that requires a blood and marrow transfusion (including the stem cells that give rise to new blood) from a donor. The finding is that after this treatment, the blood of the patient continues to show the methylation age of the donor, not the patient.

Epigenetic Aging and Telomere Aging Bound to a See-Saw Relationship

(This was the most exciting new result for me personally, because it relates to an idea I have held dear for more than a decade.)

Methylation age is older or younger than chronological age in different people, generally by about +2 years. 40% of the variation is due to genetics. Some common genetic variants can make the clock run faster or slower. The most prominent genetic variants link telomere aging to methylation aging. The faster your epigenetic clock runs, the longer your telomeres. The slower your epigenetic clock runs, the shorter your telomeres. [preprint]

There’s a word for this in the genetic theory of aging. It’s called Antagonistic Pleiotropy. Back in 1957, George Williams theorized that the genes causing aging ought to have simultaneous beneficial and detrimental effects. That would explain why natural selection has permitted aging to occur, despite the fact that it cuts off fitness. Williams said: Nature had no choice but to accept the genes that cause aging because there was no other way to get the benefits of these same genes (which he surmised ought to enhance fertility).

My theory of Antagonistic Pleiotropy is that it is not a situation of “forced choice”; rather, aging is important for the health of the community, and mother nature has been faced with the dilemma: how to keep aging in place despite efficient natural selection against it on the individual level. Aging is so important to the community that evolution has been motivated to find ways to keep it in place, despite the short-term temptation for natural selection to favor those with longer lives (thus greater opportunities to leave offspring). In my hypothesis, evolution invented pleiotropy to address this problem. The telomerase-epigenetic clock connection is an example. There is no physically necessary connection between telomerase and epigenetic aging, but the two have evolved a see-saw link so that it is more difficult to mutate aging away.

This also relates to my coverage last fall of the telomerase-cancer connection. At the time, I was scratching my head, why should genetic variants that lengthen telomeres be associated with higher rates of some cancers? Here is a clue: The same genetic variants that lengthen telomeres also accelerate the epigenetic aging program. The specific example of a cancer that is most closely tied to higher telomerase levels is melanoma, which is a cancer that is less sensitive to age than other cancers. People tend to get melanoma earlier in life than other skin cancers. Therefore, I predict that other pleiotropic links will be found between these genetic variants that promote longer telomeres and other mechanisms linked specifically to melanoma.

The Bottom Line

All these data in a field so new is a tribute to Horvath’s industriousness and to the promise and fruitfulness of a new methodology.

The data so far suggest that methylation programming is a big part of the driver of aging, but not the whole story. Smoking affects life expectancy, but it doesn’t affect methylation age. Weight loss benefits life expectancy, but it is invisible to methylation age. Most curious are those children who fail to develop, or age prematurely, even though their methylation age is progressing on schedule.

What does it mean that radiation ages the body without advancing the methylation clock? Perhaps that accumulation of damage is part of the phenotype of aging, though I remain hopeful that the body remains capable of undoing that damage even late in life, if it is re-programmed to want to do so. What does it mean that AIDS advances the aging clock? Perhaps that the immune system is a central signaling mechanism in the aging process.

So, it’s “methylation plus”. Plus what? Not just methylation plus damage”; though we can certainly shorten our lifespan with radiation or smoking, we can’t increase our lifespan by avoiding toxins. “Methylation plus other epigenetic programs”—this would be my first guess. “Methylation plus mitochondrial state” would be a close second. Methylation is all in the nucleus, and the cytoplasm of the cell seems to store independent information, and can even re-program the state of the nucleus, as suggested by parabiosis experiments. There is also evidence for“Methylation plus telomere shortening”.

We now have many effective interventions (mostly of small effect) for longevity and preventive care. Most readers of this blog take more than one supplement each day; some of us (I confess) take very many. We make an unthinking assumption that “more is better”, or rather that if A is beneficial and B is beneficial then if we take A and B we can get the benefits of both. We don’t think to question or deconstruct this reasoning. It is rooted in a reductionism that works pretty well in the physical sciences, much less well in biology.

We know that the benefits of all these interventions don’t just add up like numbers in a spreadsheet, but we continue to act as though this were our reality.

The truth is that we know almost nothing about the cross-talk among different health interventions. The reasons so few experiments have been done are plain enough, but the situation has become untenable. There is an urgent need to understand the interactions among treatments. We might begin with those that are individually most promising, but expect surprises. The combinations that offer the greatest longevity benefits may turn out to be pieced together from components that individually have little or no effect.

I might have said ‘the most promising way forward for medical research today, because I believe that anti-aging science is the most productive area of medical research. If you are reading this page, you probably know this already, but we all take comfort in confirmation of what we already know. So:

Prevention is more cost-effective than treatment. The root cause of most disease in the developed world is aging. This point has been made decisively [for example], most eloquently by Aubrey de Grey. (The root cause of most disease in the third world is poverty, and ending poverty is also an essential imperative, but it is not a subject for medical research.)

The problem of interactions has been neglected for a number of reasons:

Unconscious linear thinking

The dizzying number of combinations that need to be studied

The want of a guiding paradigm that would provide context for individual studies

Scientific inertia: researchers are more likely to study (and funders are more likely to support) research programs that are established and proven

But the problem is potentially of great import. We expect a great deal of redundancy among the mechanisms of action of various interventions we know about. Taking two or three or four drugs that address the same biological pathway is likely to be a costly waste. More rarely, longevity drugs may interact in ways that actually interfere and reduce overall effectiveness.

But we have good reason to hope that in rare cases there are combinations that are more than the sum of their parts. These fortuitous combinations synergize to offer greater benefits than they provide separately. Finding a few such combinations would be a jackpot that justifies many, many expected null results.

The huge number of possibilities to be covered

If we begin with 30 individual interventions, there are 435 pairs of interactions and 4060 combinations of three and 27,405 combinations of four. If we think traditionally, each one of these combinations is a research program in itself, requiring at least several person-years of professional effort plus overhead. This is the daunting reality that confronts anyone who is intent on beginning to address the problem of interactions. 27,405 experiments of any kind is a labor of Hercules, even for a well-funded, fully roboticized biomedical lab.

There is a hierarchy of experimental models for studying anti-aging interventions:

Human cell cultures are the cheapest and fastest, but we learn the least

Complementing human cells are yeast cells, which actually have a life expectancy and some biology that overlaps our own

Studies of thousands of C. elegans worms can be done efficiently with robotic controls and worm counters.

Fruitflies are a great deal “more like us” than worms and they can be raised in large numbers, live just a few weeks.

Lab rats and mice are expensive, but they are mammals with biology that is much like our own. Experiments in rodent longevity last 2 to 3 years.

Human trials require extensive safety measures and typically take decades to see subtle changes in health and mortality statistics; but this is the most direct indication of what we want to know.

So, how might we begin?

We have no idea what we will find. Maybe there will be a few spectacular combinations. Maybe the interactions will turn out to be small, mostly negative, and boringly expected. (My guess is that both of these will turn out to be true.) We should not try to define the second stage of the program until we have results from the first.

The first step is to choose the most promising interventions to combine. A great number of drugs and supplements are known that extend lifespan in rodents and/or lower mortality in human epidemiology. Magalhaes and Kaeberlein have put together a large database of animal studies that seems to be off-line at present. Another version is live at this address. Here is a list I proposed in this column two years ago:

Rapamycin

Aspirin

Metformin

Melatonin

Deprenyl

ALK5 inhibitors

Epitalon/Epithalamin

MitoQ/SkQ

Beta Lapachone (Pao d’Arco)

Spermidine

Berberine

Dinh lang (Policias fruticosum)

Pterostilbene/Resveratrol

Gynostemma pentaphyllum (jiao-gu-lan)

N-Acetyl Cysteine (NAC) / Glutathione and precursors

Ashwagandha

Turmeric/curcumin

C60

Oxytocin (not oral)

J147 (a promising new Alzheimer’s drug)

NR, NMN and NAD precursors

We might add

Polyphenols from tea

Flavinoids from blueberries

Angiotensin inhibitors

NLRP3 antibodies

Acetyl L-Carnitine

Piracetam

DHEA

Statin drugs

Cardarine / GW501516 / PPAR agonists

Dasatinib / Quercetin

FOXO4-DRI

Astaxanthin

Momordica charantia (bitter melon)

Gotu kola / Bacopa

Reishi mushroom

Astragalus extracts

Pine bark extract

Ginseng

Acarbose

BHT

Interventions not in pill form include

Exercise

Caloric restriction

Intermittent fasting (various schedules)

Plasma transfusions from younger individuals

Platelet-rich plasma

Transplanted young thymus

Transplanted young suprachiasmatic nucleus

How to prioritize and explore the huge number of combinations? Here are four ways we might begin to sort through the possibilities:

Statistical mining of an on-line registry of what people are taking presently

Let’s look at these one at a time.

1. Biochemical Theory

We know a few biochemical pathways that are linked to longevity. They all overlap and talk to each other. Nevertheless, we expect that treatments that address the same pathway are likely to be redundant, whereas treatments that address distinctive pathways have a better chance of synergizing. For example, insulin resistance is a robust hallmark of aging. The insulin pathway is most plastic and most accessible to intervention. Fasting and caloric restriction address the insulin pathway, as do metformin berberine, jiaogulan and bitter melon. Exercise has many benefits, some of which work through the insulin pathway.

We might continue classifying interventions that address other pathways. Here are some longevity pathways of which I am aware:

Insulin

mTOR

Inflammation

Immune senescence / thymic involution

Epigenetic reprogramming / transcription factors

Mitochondrial senescence

Autophagy

Anabolism / Catabolism imbalance

Telomere attrition

P53 / Apoptosis

Someone who knows more biochemistry than I do might be willing to classify the interventions I list (and others) according to these 10 pathways (and others). Here is a template in Google Sheets, which I establish as an open Wiki. http://tinyurl.com/longevity-pathways

2. Eastern and Indigenous Medical Traditions

Many useful modern medicines are derived from ancient folk wisdom. But this work has proceeded with a deductive logic, isolating active chemicals from whole plants (as aspirin from willow bark, cycloastragenol from astragalus, and curcumin from turmeric). Many folk traditions, especially Traditional Chinese Medicine, are based on not just whole herbs but combinations of herbs that have been found over the ages to work together. Ideas may be taken from these traditions to prioritize combinations for testing. For example, the best known Chinese longevity formula is Shou-wu-chi (首乌汁;), which is compounded of (list from Wikipedia):

The Ayurvedic tradition is less contains fewer formulas, but combinations that are said to contribute to longevity include these (which I found, just for illustration, at Banyan Botanicals)

Haritaki (Terminalia chebula)

Guduchi (Tinospora cordifolia)

Amalaki (Embelica officinalis)

Kumari (Aloe barbadensis, or aloe vera)

Guggulu (Commiphora mukul)

Brahmi or gotu Kola (Centella asiatia) or closely-related Bacopa

Ashwagandha (Withania somnifera)

3. Broad screens for particularly effective combinations

Two years ago in this space, I proposed a screening protocol in which all combinations of 3 interventions from a universe of 15 would be tried on just 3 mice each. I showed with a computational model that if these included at least one lucky combination that increased longevity by more than 50%, then, despite the small number of mice, it would be identified with at least 80% confidence. Combinations of three from a universe of fifteen is a kind of sweet spot for this particular experimental design, and much less is learned if the numbers are scaled back. This means it is not feasible to test the concept on a small scale. The full proposal requires 1365 mice in cages of three, followed for at least two years. Cost estimate is about $2 million in the US or Europe, perhaps as low as $500,000 to do the same experiment in China. I would be eager to work with any lab that has the expertise and the facilities to implement this protocol. The experimental design and simulated analysis was recently published in English in a Russian journal.

4. Data-mining of an online registry where people record what supplements they are taking and commit to reporting their health history

It would be a great public service if someone were to establish a web-based registry where individuals could share information about what supplements they are taking and what results they are getting. Over years, this could turn into a data miner’s heaven for information about individual drugs and lifestyles and their interactions. The subject is too big for a controlled experiment, but enlisting the public would be a great and greatly-rewarding project.

I know there are web sites such as Longecity that are excellent resources for anecdotal accounts of others’ experiences. But the data is not in a format that lends to statistical summaries. If you know of an existing online database of this sort, please reach out and share the web address with me.

I have preliminary plans to create such a web site in conjunction with a forthcoming book project.

The Challenge

There may already be a viable plan for major life extension hiding in plain sight. There is no extant research program to explore the relationships and interactions among life extension measures. Eventually, some large, well-funded agency (perhaps NEA or the Buck Institute) will take on this project in a systematic way. But the large organizations are conservative, and are unlikely to begin until the ice is broken. Thus, even the first shards of information in this area are likely to be valuable indications of a new research direction.

If you have a research lab, or if you know are connected to someone who might be interested in this project, or if you have a funding source, please let us work together.

My book (with Dorion Sagan) has just been released as a Kindle edition in the UK, Australia and New Zealand, Hong Kong, Russia, Singapore and various European countries. The book is sold in America by Flatiron/Macmillan as Cracking the Aging Code. The British edition is called What Good is Death?

Life Extension Foundation has just announced that next week they are going to announce a partnership with the Young Blood Institute for what is perhaps the most ambitious human trial of anti-aging medicine ever. It’s a daring project, with what is IMO a most promising target. But I find details of their protocol puzzling, and haven’t been able to get satisfying answers from LEF or from YBI about why they’ve made the choices they have, and how they will be able to learn from the project.

Extensive testing is planned, including telomere age and methylation age in addition to a full battery of standard blood tests like lipids and inflammation markers.

The program is self-funded by research subjects, with projected cost ~ $50,000 per participant.

In each transfusion procedure, red and white blood cells will be separated and cycled back into the subject. Blood plasma with dissolved blood chemicals will be removed. It will be replaced not by full plasma from a donor but by albumin and gamma globulin only.

“Rescue Elders” project of LEF

Last year, Life Extension Foundation announced a new and ambitious program of human experimentation at the edge of medical science, sponsoring high-risk trials to prospect for anti-aging breakthroughs in the near term. (The project’s name, Society for the Rescue of our Elders, was taken from an 18th Century group in Amsterdam, Society for Recovery of Drowned Persons, that was formed after the efficacy of artificial respiration was first discovered.) Their first project was a clinical trial of rapamycin, now ongoing. This present program of plasma transfusions is their second project.

Target: Epigenetics

It’s my belief that the body’s primary aging clock is epigenetic. That is to say, different combinations of genes are expressed at different times in life, and in old age the constellation of genes that is turned on causes inflammation, auto-immunity, and a preponderance of anabolism over catabolism. The master’s tools are deployed in old age to dismantle the master’s house.

As a general concept, I think this is the best working hypothesis we have. But if it is correct, it doesn’t offer an immediate key to rejuvenating the body. The problem is that epigenetics is enormously complicated. (The genetic code, in contrast, is as simple as it can be—a code of correspondence between triples of nucleic bases in the DNA with the 20 amino acids that are linked together, then folded to form proteins.)

Methylation of chromosomes is the best-known and first-discovered mechnism by which genes are turned on and off. In addition to methylation, there are dozens of other epigenetic markers and signals that are applied directly to DNA or indirectly to the histone spools, beads of protein that around which DNA is coiled.

Different genes are turned on in different parts of the body. This is the primary way that the body differentiates one kind of cell from another—they all have the same genes, but different combinations of genes are turned on in a nerve cell or a muscle cell or a skin cell. Overlayed on these differences from one cell type to another, genes are turned on and off with age. This effect is reliable and consistent enough that Steve Horvath was able to construct a methylation clock based on 353 methylation sites that change consistently with age across all cell types in the body.

The connection to blood signals was supplied by research from Stanford, Berkeley and Harvard, in which blood from a young mouse is introduced into an old mouse, and is shown to rejuvenate its tissues, stimulate new growth, and promote healing. With a small conceptual leap, I imagine that there is a self-regulating epigenetic clock distributed through the body. On the one hand, epigenetic markers in each cell give each cell its characteristic age. On the other hand, these same cells are sending signals though the blood (transcription factors) that are continually updating the epigenetic program and keeping it in sync throughout the body. The hope is that (even if we don’t understand in detail how the epigenetics is programmed) the substitution of a young blood environment for an older blood environment will reprogram epigenetics in the distributed cells, and after a few cycles it will be self-sustaining. That is, once the cells are reprogrammed to be younger, they will themselves send signals into the blood that maintain the younger state.

Criticism of the protocol

Here is a description of the proposed YBI protocol. Six times over a period of 4-6 weeks, patients will be hooked up to a plasmapheresis machine. Whole blood is removed from one arm, and a mixture is returned to a vein in the other arm. The mixture that is returned will include all the patient’s own red and white blood cells. But the blood plasma, clear liquid with all the dissolved signal molecules, will be removed. The plasma will not be replaced by blood plasma from a younger patient, as in a standard plasma transfusion. Instead, the return side will contain only albumin and gamma globulin. These are the hydrostatic and immune components of the plasma (antibodies). The theory is that auto-immune aspects of aging will be addressed in this way…but the antibodies are generated continually by white blood cells, so that the treatment will not last long. Hence the rationale for frequent repetitions of the treatment, less than a week between treatments.

My principal fear is that the planned YBI protocol may be able to do only half the job. My conjecture is that it is the signal molecules that actually maintain the epigenetic program. The proposed protocol will remove the bad ones, and that’s half the job. It may be that there are transcription factors from young blood that are deficient in the old and need to be replenished. Full plasma transfusions from young donors would do both, fully replacing the blood environment of an old person with the blood environment of a young person. But it is expensive and requires many donors for each patient. It is to control expense that YBI has chosen to do do the removal, but not replacement of blood signal molecules.

Just last year, Tony Wyss-Coray headed a Stanford trial for AD, through a for-profit spinoff called Alkahest. Alzheimer’s patients were given four doses of young blood plasma. But the dose was small, a total of 1.5 liters of plasma, and the bad actors weren’t being removed. Results were disappointing, but perhaps this is because the procedure was not bold enough.

Promising Precedent

Beginning in 1924, a Soviet Bolshevik named Alexander Bogdanov experimented on himself, receiving a series of 10 blood transfusions from younger donors. He was 51 years old at the start of the experiment, and contemporaries report that he appeared physically ten years younger in the course of the procedures. He self-reported prodigious health benefits and return of youthful vigor. The experiment ended tragically in 1928, when he received blood from a student who had been infected with malaria, and died of the infection.

Harold Katcher has been thinking about the rejuvenation potential of plasma transfusions for a long while, and here is the protocol he suggested five years ago. He does not speculate about what schedule would be ideal, and he cautions us that extensive experimentation with mice and even in cell cultures would be useful before beginning human trials.

Unpromising Precedent

Two years ago, I spoke via skype with Jesse Karmazin (Stanford University and Ambrosia). He told me that as a med student he had done an analysis of historic data from transfusions performed at Stanford University Hospital, and found that those who had received blood from young donors had better outcomes and better long-term survival rates than those whose blood had come from older donors. I was very interested in this claim, and asked him for the data that supported it. He told me it could not be released for reasons of patient privacy. I never did get to see that data, and he never published his analysis.

Last year, a published study claimed the opposite: that in a large database of Swedish and Danish patients transfused between 1995 and 2012, they were unable to detect any survival difference between those who received blood from young donors and a matched group of patients whose transfused blood came froun old donors.

Questions

Ideally we would like to learn many details from a trial of HPE (heterochronic plasma exchange). Fundamentally, we would test the basic question whether circulating factors in the blood are indeed able to reprogram the epigenetics of cells throughout the body, and whether this will have a salubrious effect on vitality, appearance, metabolism and the immune system. A well-designed trial might also teach us more

How long does the young plasma profile remain in the bloodstream before the body’s old cells take over and drag the proportions back down to where they were? (At this point, the next infusion would be appropriate.)

How many transfusions are required before the body’s cells are reprogrammed, and the young plasma profile becomes self-sustaining?

Transfusions from young donors are a good place to start, but obviously not a practical solution for rejuvenating large numbers of people in the long term. But if we can learn which chemical constituents need to be removed and which need to be added, it is possible that a core handful of such factors might be discovered. Those that need to be added can be manufactured in bulk by vats of genetically modified E coli. Those that need to be removed can be targeted with antibodies and removed in a simplified blood filtering procedure. This is a promising research path—perhaps the most promising that is visible from where we are now. But we’ll never know if it can work until we do an expensive and time-consuming series of experiments.

How many transcription factors need to be regulated in order to the job? This is the biggest unknown. When I spoke with Irina Conboy four years ago, she was optimistic that the number may be less than ten, but last year, she was less optimistic. I take heart from the fact that just four Yamanaka factors can turn a differentiated cell into a zero-age stem cell.

Toward the future

Plasma transfusions are a safe, approved medical procedure, used for decades as treatment for (especially) auto-immune diseases. No FDA approval would be needed for a clinical trial, using transfusions “off-label” to test rejuvenation potential. However this is not a project likely to be picked up by venture capitalists looking to make a quick buck. The first reason is that the process will be expensive and time-consuming, with a great deal of trial and error. The second reason is that when it is all over, everyone will know what are the best schedules and procedures, and the most important transcription factors in our blood—but it is doubtful that this will be patentable intellectual property, or that the investors would be able to maintain a trade secret. What we need is a substantial public investment or a middle-aged billionaire angel investor who is thinking clearly about his own destiny a decade or two down the road.

Like you, dear Readers, I tend to be focused on the biochemistry, and have to remind myself again and again that the mind and body are intertwined. I came out last week with my core belief about biology: Mechanistic physics explains only half of what we are. Life has its own laws which we will discover only if we admit they exist.

In fact, the most powerful thing we can do to prolong life expectancy is to have robust connections to other humans. The best-documented effects are for empowering relationships with community (especially cooperative action for change) and intimate relations of love. Together, these factors contribute more to life expectancy than any diet or exercise program, or any supplements you can take. The difference is comparable to life expectancy difference between heavy smokers and non-smokers. (I wrote about these topics 2 years ago: [1. Social status and depression, activism vs powerlessness, 2. Family]

Elissa Epel is famous for having elucidated the connection between stress and eroding telomeres. But she has also brought us positive messages: Meditation is associated with telomerase expression and longer telomeres. Altruism breeds telomerase. Loving-kindness is associated with longer telomeres. In a publication last summer, she and co-authors documented the benefits of sex. Women (all subjects were partnered females) who had sex at least once in the week surveyed had longer telomeres than women who did not.

The result added to evidence that goes back at least 20 years. The Caerphilly study showed that frequency of sex correlated with lower all-cause mortality in men. The conclusion extends to women. The tendency of medical professionals to interpret the result in terms of the biochemistry of orgasm has been tempered, as it became clear that sex with a partner, with or without orgasm, has benefits above masturbation [ref]. Intimacy without sex has its health rewards, as does the strength of one’s community fabric.

So, in this context, the headline result from the newest study is no surprise. The puzzle is that, even though powerful connections between social relations and health are confirmed again and again, the details keep changing, and consistency is elusive.

For example, the study just cited found that subjects who reported more sexual activity had longer telomeres, but they didn’t have more telomerase activity. In fact, they had (almost statistically significant) less telomerase activity. This was a short-term study. Telomerase activity is a short-term variable, and telomere length is supposed to respond in the longer term to telomerase activity. We should not have been surprised if an increase in telomerase had been observed, without a significant difference in telomerelength. The opposite finding suggests a missing link in the causal chain. (The Discussion text in the article is very open about this mystery.)

The study included only women. Women have been found to be more sensitive to the quality of loving attention and the depth of their connections in love, while men tend to respond to the cruder quantitative variable of sexual activity [ref]. But for women in this study, telomere length was related only to the frequency of sex, and not to the quality of relationship, or to relationship satisfaction. In fact, they found no significant association with any of the subjective questions asked concerning satisfaction with the relationship, or feelings of closeness. Again, the investigators themselves were surprised.

Paradoxical results from other studies: Men (>57yo) who had frequent sex (more than once per week) and men who self-reported that sex was “extremely satisfying” had twice as many heart attacks in the ensuing five years [ref]. In the same study, results for women were not strong enough to be statistically significant, but were strange enough to be puzzling. Women (>57yo) who reported sexual relations that were highly satisfying had higher risk of cardiovascular disease, but women who reported most intense pleasure from sex had lower risk. “These findings challenge the assumption that sex brings uniform health benefits to everyone.”

This classic study found that marriage offers substantial benefits in life expectancy for both men and women, but that the benfits for men are far larger. The relative risk in mortality rate, unmarried vs married, is 1.5 for women but 3.5 for men. The large disparity has not held up in more recent studies.

This is the most comprehensive recent review of the relationship between social variables and all-cause mortality, but it is confusingly written (I believe the verbal interpretation of statistics is incorrect). The message comes through loud and strong, that social integration accounts for a large benefit in decreased all-cause mortality, accounting for 5 to 10 years of life expectancy. But even more than in other fields of social science, there are contradictory results and inconsistencies that thwart anyone trying to tell a neat story.

Why is social connection so important to health

“Two main types of models have been proposed to explain how social support influences physical health. In main-effect models, high levels of social integration are health promoting, regardless of whether one is under stress [ref, ref]. Greater integration into one’s social network gives an individual identity, purpose, and control, a perceived sense of security and embeddedness, and a source of reinforcement for health-promoting behaviors or punishment for health-compromising behaviors, all of which can promote health [ref]. In the stress-buffering model [ref], the negative effects of stress occurring outside of one’s social relationships (e.g., at work) are diminished by the presence of strong social support, which can mitigate stressful events directly (e.g., intervening on a friend’s behalf) or through reducing stress appraisals [ref].” [quoted from Robles, 2004]

Bert Uchino distinguishes between “perceived support” and “received support”. The correlation of the former with health and mortality variables is robust. But the latter is sometimes found to be inversely correlated with health. This seems to say that if people are helping you and you don’t appreciate it, you’re worse off than if you had been on your own. If you think you’re embedded in a caring and supportive community, you’ll live longer. If you’re actually embedded in a caring community, but you devalue what you’ve got or if you isolate yourself because you’re more comfortable that way, your life expectancy is shortened. This is a morality tale if I ever heard one.

Conflictual interactions in the context of marriage (as in Western culture generally) contribute to higher levels of systemic inflammation [ref]. But this study found no relationship between job stress in men and measures of chronic inflammation. Maybe it depends on what is meant by “stress”. This study suggests that feeling out of control (powerlessness, low status) is associated with markers of inflammation.

Perspective

Why do we care about this? Many of us are fanatical about following the best evidence when designing exercise and supplement regimens for ourselves. But is there anyone out there who is waiting for the latest correlation with telomere length before deciding whether to fall in love? (I didn’t think so.)

No, the reason we care about this subject is that it reminds us that aging is a social process almost as much as it is a biological process, even if the social correlates of longevity confound our best intuitions about how to live well.

And perhaps it reminds us, indirectly, that in the “rationalization” of our health care system, we have made a bad bargain. Over the course of my lifetime, medical practice in America has gone from a model of individualized care by family doctors to impersonal care by specialists. Medical care has become more evidence-based, and there is a much better chance that the doctor who treats your condition has a deep knowledge and experience of that condition. But what we’ve lost along the way is the doctor-patient relationship—both because you see a different specialist for each condition, and also because as doctors’ time is squeezed to optimize profit, the time for listening and empathizing has been eliminated. Despite the accumulation of studies showing that doctor-patient relationship has an outsized effect on prognosis, our present health care system is systemically deficient in human caring.

This time each year, I take the liberty of posting something more speculative and personal. In this essay, I propose that everything we consider the “scientific world-view” is only half the story, and that science must expand its foundations if it aspires to be a complete account of reality.

A reductionist approach to science has become so ubiquitous that many scientists find it difficult to imagine that science can be done in any other way. Interactions among elemetary particles are the ultimate explanation, the only final cause. Biology can be reduced to chemistry. Chemistry is the science of large numbers of atoms, interacting according to the laws of quantum physics.

But reductionism is only a habit of the way we do science. It is logically possible that there are global laws, interconnections, entanglements; and that these are discoverable by investigation that is rigorously scientific . Teleology is commonly dismissed as “unscientific”, but it is precisely teleology that we may need to explain a host of diverse findings that conventional science has swept beneath the carpet.

One of my oldest friends is a professor of computer science at a great mid-western university. An Israeli-American, Uri is descended on his mother’s side from an ancient line of Kabbalist mystics, but his philosophy is strictly materialist. He believes that “the mind is what the brain does”, that the brain is a computer, and that electronic computers can be programmed to do anything that our brains can do. Like a great majority of computer scientists, he believes that subjective consciousness is something that arises when computation attains a certain kind of complexity.

Last summer, Uri told me a story from his youth. In college, he had dated a young woman, a passionate political activist. Years after he had lost touch with her, she sunk into depression with the election of Ronald Reagan. Uri awoke one night, sweating and screaming, from a nightmare in which she had jumped from a building. Though he had not talked to her in several years, he reached out and tried to contact her the next morning, and her parents informed him she had killed herself that very night, jumping from the window of her apartment. Uri was shaken at the time, but he has filed the experience in his memory as a coincidence, a curious anecdote with no particular message about the way our world works.

Sitting in a canoe, listening to Uri’s story, I asked him if he thought an artificial intelligence might ever have such dreams. What would he think if his story and many like it were collected in a stastical database, and it could be demonstrated that such “coincidences” were far too frequent do be dismissed, that their composite probability was far rarer than “five sigma” (roughly “one chance in a million”), which is a conventional threshold for announcing that physics has discovered a new particle. He responded thoughtfully: He didn’t have time to do that kind of analysis. It depends on so many people’s stories, and people’s memories of such things aren’t so reliable. But if it could be established, he said, he would be forced to conclude there were new sub-atomic forces that brains can use to communicate, and that physics had not yet discovered. In any case, he was committed to the idea that reality is physical — space, time, matter and nothing else — and that every phenomenon of nature must be explainable in reductionist terms. By definition.

How Science came to be narrow-minded, with universal ambitious

Don’t doubt the Creator, because it is inconceivable that accidents alone could be the controller of this universe.— Isaac Newton

Newton’s scientific ambition was prodigious. He first conceived the idea that the universe was governed by precise mathematical laws that were independent of place and time. But he never imagined that physics was a complete picture of the world. It was only in the 19th Century that the idea took hold that physical law might explain everything. Science had been enormously successful in accounting for diverse phenomena, expanding again and again to explain more of our world. Then scientific philosophy made an audacious leap: Every phenomenon in our universe is regular. All of our experience can be accounted for in terms of deterministic mathematical laws.

Is this statement true? We all assume it is. But in fact, it is an empirical statement, a bold one, to be sure, and all the more reason it should be challenged and tested experimentally.

Of course, it’s not literally true that two experimenters doing the same experiment always find the same result. There’s experimental error—mistakes and misjudgments that enter any human enterprise. And in biology, there is the complication that no two organisms are exactly alike. These things were understood and accounted for in the Nineteenth Century. This was the time when “vitalism” was stripped out of biology, and living things were boldly assumed to depend on the same mechanistic laws as non-living matter. Biology was conceived to be built upon chemistry, and chemistry could be understood as the interactions of atoms. It was at the level of atomic physics that the Universal Machine operated in a manner precisely determined by mathematical laws.

But 20th Century science shattered determinism. The Scientific World-view retreated just far enough to allow for quantum randomness and the Heisenberg Uncertainty Principle.

“Philosophers have said that if the same circumstances don’t always produce the same results, predictions are impossible and science will collapse. Here is a circumstance that produces different results: identical photons are coming down in the same direction to the same piece of glass. We cannot predict whether a given photon will arrive at A or B. All we can predict is that out of 100 photons that come down, an average of 4 will be reflected by the front surface. Does this mean that physics, a science of great exactitude, has been reduced to calculating only the probability of an event, and not predicting exactly what will happen? Yes. That’s a retreat, but that’s the way it is: Nature permits us to calculate only probabilities. Yet science has not collapsed.”

— Richard Feynman

To Einstein’s consternation, God does play dice with the world. When the Twentieth Century discovered quantum indeterminacy, most philosophers of science made the minimal modification to their deterministic picture. To them, the future state of the universe is determined by its present state plus pure chance. In this paradigm, there is nothing outside physics, or if there is such a thing as “soul” or “spirit” or “free will”, it is irrelevant to science and to experience. It can have no observable effects, because the physical universe is a closed system, governed perfectly by a combination of deterministic laws and pure chance.

This is the philosophy of “materialism” or “physicalism” that has become synonymous with the scientific world-view today. But it is far more explicit than the original scientific world-view, which says only that our knowledge of the world depends on empirical observation plus mathematical logic. In fact, the original scientific world-view is a system for discovering truth, but it is silent about what that truth ought to be. This expanded scientific world-view is not just a statement about methods, but contains a description of the nature of the world. It is a scientific theory, in the sense that it says something about the empirical nature of reality. Like all scientific theories, the expanded scientific world-view can never be proven true, but it can be falsified by observation.

The original scientific world-view as bequeathed to us by the Enlightenment is an epistomology which we can accept or reject, but no arguments can be adduced for or against it. The expanded scientific world-view is a statement about the world, and we may legitimately ask, “Is it true?”

Reproducibility

The issue of reproducibility is the crux of the matter, and it is related to science in two ways.

On the one hand, science seems to depend on reproducibility, at least in the statistical sense. If different experimenters at different times and places get different results from the same experiment, how can we ever hope to come to agreement about the world we live in? Reproducibility—in the expanded, statistical sense—seems to be a necessary feature of the world if we are to be able to study the world with science.

On the other hand, we may treat reproducibility as an empirical question. Is it true that the same experiment always results in the same results, at least statistically? To rephrase more provocatively: Is it true that the universe is governed by scientific laws that always hold true, or are there exceptions and one-off happenings, things that occur sometimes but without a regularity we can codify?

We might ask, “are miracles real?” Should the scientific world-view take a firm stance on this issue and answer, “No!”? Or should science be open-minded, and consider the possibility that those who report miracles are not always deluded or mistaken?

Evidence that we need a new model

From one stage of our being to the next
We pass unconscious o’er a slender bridge,
The momentary work of unseen hands,
Which crumbles down behind us; looking back,
We see the other shore, the gulf between,
And, marvelling how we won to where we stand,Content ourselves to call the builder Chance.
— James Russell Lowell

There is no shortage of credible reports that cannot be explained by the reductionist paradigm of science, but most have been shunted out of the mainstream journals, attacked or simply ignored.

Perhaps you have had a dream or premonition similar to Uri’s. If not, you probably know someone who has. It has become common for scientists to dismiss “anecdotal evidence” without feeling a need to explain it. This comes from a ubiquitous assumption that all experiments are replicable — exactly the assumption which I think we need to challenge.

Daryl Bem is an emeritus professor in the Cornell Psychology Dept, recently retired after a long and distinguished career doing mainstream research about stimulus and response. In one of his last publications, he broke into a well-regarded psychological journal with an article that documented responses in human subjects that preceded the stimulus. This is precognition. The subject’s subconscious knew or sensed what image was about to appear before him on a computer screen. Julia Mossbridge summarized a substantial body of research, which collectively corroborates the reality of precognition with 99.999999999% certainty.

Robert Jahn, retired dean of the engineering school at Princeton University stumbled (through his student’s term project) upon evidence for the ability of human intention to affect probabilities that ought to be “quantum random”. Jahn had the curiosity to investigate further. When the anomaly wouldn’t go away, he refined the experiment and collected data over 30 years, by which time his results had achieved 5-sigma statistical significance — on a par with evidence for the Higgs Boson. Jahn was ostracized and ridiculed, and colleagues began to discredit his work in aerospace engineering based on his willingness to openly consider the possibility that the human mind might be able to affect quantum processes outside the organism.

Dean Radin has conducted a broad array of experiments that demonstrate different aspects of telepathy, precognition and telekinesis. He has a background in physics, and routinely takes extraordinary measures to guarantee the isolation of his experiments from extraneous physical influences. In one recent project, he found that focused attention of a person who is not in physical contact with the equipment can shift interference fringes of laser light passing through two slits. This connection between thought and quantum is akin to results reported by Jahn.

Outside the world of parapsychology, there are uncontroversial animal behaviors that defy explanation. Fish, turtles and cetaceans routinely navigate thousands of miles through the ocean, their guidance system unknown to science. Each fall, a generation of Monarch butterflies is able to retrace the 2,000-mile migration path flown by their great, great, great grandparents six months earlier. Flatworms have been conditioned to respond to light, then they are ground up and fed to other flatworms, who acquire some of the conditioning through cannibalism [skeptic’s account].

Dozens of labs around the world have successfully replicated the cold fusion experiments of Pons and Fleischmann. Reports of their work are sequestered in this on-line journal because mainstream physics journals have declared that cold fusion is impossible. In fact, there is nothing in fundamental physics that precludes cold fusion; it is, after all, a highly exothermic reaction, and the energy release is exactly as predicted. But cold fusion implies a new bulk quantum effect (akin to superconductivity, superfluidity and lasers) for which there is yet no theory. [video summary] The physicist who taught me quantum mechanics at Harvard was a Nobel laureate who became irate when the American Physical Society refused to publish his proto-theory of cold fusion.

Ian Stevenson and Jim Tucker are medical doctors who have each spent decades investigating cases “suggestive of reincarnation”. Children recall past lives, with details about the circumstances of that life that are later corroborated. Stevenson noted the frequent presence of birthmarks where former selves suffered trauma at death. Helen Wambach and Carol Bowman have used hypnosis to help adults find access to information about past lives.

The ganzfeld protocol is the most reliable experimental procedure for demonstrating telepathy. A meta-analysis of 59 ganzfeld studies reports a combined success rate of 30% in identifying a target photograph when the chance hit rate should be 1 in 4. The improbability of this result has been calculated in different ways, with results from 10-12 to 10-8.

Through a glass darkly: Where post-reductionist science is headed

All the progress in science since the Enlightenment has built on a reductionist paradigm: breaking down the whole into parts, explaining the parts in terms of influences that are nearby in time and space. If this is not the whole story, then we might imagine there are relationships among distant events. There might be large-scale patterns that cannot be explained as “emergent” from local laws. There may relationships that appear to us as retrocausality. There might be destiny.

It is clear to me that what physics calls “quantum random” is not random at all, but rather is determined non-locally, via quantum entanglement. Events distant in time and space are linked in a manner that baffle our usual methods of scientific inquiry, but that may be discoverable by a new kind of science.

There is nothing un-scientific about such a hypothesis, and in fact quantum mechanical “entanglement” suggests that such patterns must exist. David Bohm has laid foundations for a science based on holistic patterns in an Undivided Universe. He offers us a beginning toward understanding an “implicate order” that may complement the explicit order in time and space that is the basis of all of mainstream physics.

The Constellation, by Joan Miro

Possibly related is the idea that mind has an existence separate from matter, that free will operates in a sphere that is able to influence matter on a quantum level. This could be a resolution in Cartesian dualism of David Chalmers’s hard problem. One link between the realm of the self outside of space and time and the realm of physical matter could be through the quantum mechanics of the brain. Roger Penrose and Stuart Hameroff have proposed a model. Stuart Kauffman cites evidence that neurotransmitters in the brain are poised on a quantum knife edge where their behavior is dictated either by randomness (in the conventional view) or could this be the portal by which intention enters into physical behavior?

It may turn out that life is not an opportunistic parasite in a vast, cold and meaningless cosmos. Life may be built into the laws of physics at the very foundation. It may be that living behaviors are woven into the fabric of the cosmos. Or it may be that awareness and free will live in a realm separate from time and space, but linked to physics at the quantum level. This would be a way to resolve the Anthropic Coincidences without resort to an embarrassment of universes.

These ideas are not un-scientific, but they are difficult to study with current scientific methods. At the dawn of the Twenty-first Century, experimental science is bursting at the seams with phenomena crying out for an expanded scientific paradigm. The crisis will not be resolved by keeping speculative science out of the mainstream journals. It is not likely to be settled by a brilliant guess about the nature of reality that resolves all our anomalies in one fell swoop. The only way forward is for science to expand its methods and entertain a broad array of wild, new ideas, most of which are bound to fail. But if we open the gates to speculative ideas, if we shake off taboos about teleology and holism, if we broaden the scope of experiments and our ways of understanding them…then I trust that our collective brainpower will be up to the task of formulating a picture of the world that comprehends a greatly expanded — dare I say “wondrous” — vision of our world.